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MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011 (2011)

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Instructor: Professor John Guttag

Collection of 26 lectures given during the Spring 2011 semester of 6.00, Introduction to Computer Science and Programming. This course covers introductory computer science methods and topics. All programming assignments use Python.

View the complete course: http://ocw.mit.edu/6-00SCS11


This movie is part of the collection: MIT OpenCourseWare

Audio/Visual: sound, color
Language: English
Keywords: programming; Python; computation; function; module; parameter; tuples; lists; strings; dictionaries; search methods; object oriented programming; OOP; analytic methods; simulation; algorithm; optimization; psuedocode; numpy; dynamic programming

Creative Commons license: Attribution-Noncommercial-Share Alike 3.0


Individual Files

Movie Files MPEG4 Ogg Video
Lecture 1: Introduction to 6.00 90.6 MB 
158.6 MB 
Lecture 2: Core Elements of a Program 116.6 MB 
157.4 MB 
Lecture 3: Problem Solving 104.7 MB 
168.6 MB 
Lecture 4: Machine Interpretation of a Program 110.9 MB 
163.0 MB 
Lecture 5: Objects in Python 111.3 MB 
173.0 MB 
Lecture 6: Recursion 108.1 MB 
171.3 MB 
Lecture 7: Debugging 109.1 MB 
167.7 MB 
Lecture 8: Efficiency and Order of Growth 109.5 MB 
182.7 MB 
Lecture 9: Memory and Search Methods 105.1 MB 
179.2 MB 
Lecture 10: Hashing and Classes 101.9 MB 
165.3 MB 
Lecture 11: Object Oriented Programming (OOP) and Inheritance 111.0 MB 
153.1 MB 
Lecture 12: Introduction to Simulation and Random Walks 110.0 MB 
161.4 MB 
Lecture 13: Some Basic Probability and Plotting Data 93.5 MB 
149.6 MB 
Lecture 14: Sampling and Monte Carlo Simulation 111.2 MB 
183.1 MB 
Lecture 15: Statistical Thinking 113.1 MB 
184.7 MB 
Lecture 16: Using Randomness to Solve Non-random Problems 108.9 MB 
178.6 MB 
Lecture 17: Curve Fitting 111.3 MB 
171.1 MB 
Lecture 18: Optimization Problems and Algorithms 109.1 MB 
181.7 MB 
Lecture 19: More Optimization and Clustering 108.9 MB 
173.8 MB 
Lecture 20: More Clustering 107.3 MB 
163.0 MB 
Lecture 21: Using Graphs to Model Problems, Part 1 123.1 MB 
165.8 MB 
Lecture 22: Using Graphs to Model Problems, Part 2 106.8 MB 
161.7 MB 
Lecture 23: Dynamic Programming 116.0 MB 
185.3 MB 
Lecture 24: Avoiding Statistical Fallacies 107.6 MB 
179.4 MB 
Lecture 25: Queuing Network Models 115.0 MB 
197.5 MB 
Lecture 26: What Do Computer Scientists Do? 109.9 MB 
142.1 MB 
Recitation 1: Introduction to Coding Concepts 113.8 MB 
193.5 MB 
Recitation 2: Loops, Tuples, Strings, and Functions 133.4 MB 
209.2 MB 
Recitation 3: Lists and their Elements, Sorting, and Recursion 109.3 MB 
187.9 MB 
Recitation 4: Recursion, Pseudo code, and Debugging 109.3 MB 
190.6 MB 
Recitation 5: Quiz 1 Answers and Object-Oriented Programming 116.3 MB 
207.6 MB 
Recitation 6: Probability and Statistics 115.9 MB 
217.8 MB 
Recitation 7: Distributions, Monte Carlo, and Regressions 102.9 MB 
139.1 MB 
Recitation 8: Hierarchical and k-means Clustering 112.7 MB 
151.1 MB 
Recitation 9: Directed and Undirected Node Graphs 108.3 MB 
192.5 MB 
Recitation 10: Introduction to Dynamic Programming 83.5 MB 
130.5 MB 
Quiz 2 Review Session 273.0 MB 
390.5 MB 
Optional Recitation: Algorithm Complexity and Class Review 91.7 MB 
159.4 MB 
Image Files Thumbnail Animated GIF
Lecture 1: Introduction to 6.00 5.2 KB 
414.9 KB 
Lecture 2: Core Elements of a Program 4.0 KB 
354.5 KB 
Lecture 3: Problem Solving 6.3 KB 
397.5 KB 
Lecture 4: Machine Interpretation of a Program 5.7 KB 
375.8 KB 
Lecture 5: Objects in Python 4.8 KB 
411.6 KB 
Lecture 6: Recursion 6.0 KB 
403.8 KB 
Lecture 7: Debugging 5.3 KB 
371.1 KB 
Lecture 8: Efficiency and Order of Growth 5.6 KB 
415.5 KB 
Lecture 9: Memory and Search Methods 6.1 KB 
403.0 KB 
Lecture 10: Hashing and Classes 7.5 KB 
380.2 KB 
Lecture 11: Object Oriented Programming (OOP) and Inheritance 5.2 KB 
362.7 KB 
Lecture 12: Introduction to Simulation and Random Walks 5.8 KB 
396.4 KB 
Lecture 13: Some Basic Probability and Plotting Data 5.0 KB 
375.8 KB 
Lecture 14: Sampling and Monte Carlo Simulation 5.7 KB 
388.2 KB 
Lecture 15: Statistical Thinking 5.9 KB 
392.4 KB 
Lecture 16: Using Randomness to Solve Non-random Problems 4.6 KB 
392.0 KB 
Lecture 17: Curve Fitting 3.3 KB 
389.5 KB 
Lecture 18: Optimization Problems and Algorithms 4.9 KB 
398.6 KB 
Lecture 19: More Optimization and Clustering 5.2 KB 
395.6 KB 
Lecture 20: More Clustering 5.0 KB 
361.3 KB 
Lecture 21: Using Graphs to Model Problems, Part 1 4.6 KB 
399.6 KB 
Lecture 22: Using Graphs to Model Problems, Part 2 5.3 KB 
391.0 KB 
Lecture 23: Dynamic Programming 5.5 KB 
375.6 KB 
Lecture 24: Avoiding Statistical Fallacies 3.6 KB 
373.3 KB 
Lecture 25: Queuing Network Models 6.1 KB 
404.2 KB 
Lecture 26: What Do Computer Scientists Do? 3.3 KB 
335.5 KB 
Recitation 1: Introduction to Coding Concepts 3.1 KB 
359.5 KB 
Recitation 2: Loops, Tuples, Strings, and Functions 5.4 KB 
382.5 KB 
Recitation 3: Lists and their Elements, Sorting, and Recursion 3.4 KB 
368.6 KB 
Recitation 4: Recursion, Pseudo code, and Debugging 5.3 KB 
376.3 KB 
Recitation 5: Quiz 1 Answers and Object-Oriented Programming 4.0 KB 
370.1 KB 
Recitation 6: Probability and Statistics 3.5 KB 
346.9 KB 
Recitation 7: Distributions, Monte Carlo, and Regressions 3.4 KB 
371.3 KB 
Recitation 8: Hierarchical and k-means Clustering 3.1 KB 
348.1 KB 
Recitation 9: Directed and Undirected Node Graphs 5.0 KB 
368.4 KB 
Recitation 10: Introduction to Dynamic Programming 3.3 KB 
354.1 KB 
Quiz 2 Review Session 5.5 KB 
400.6 KB 
Optional Recitation: Algorithm Complexity and Class Review 3.0 KB 
346.4 KB 
Information FormatSize
MIT6.00SCS11_files.xml Metadata [file] 
MIT6.00SCS11_meta.xml Metadata 1.3 KB 
MIT6.00SCS11_reviews.xml Metadata 544.0 B 
Other Files Archive BitTorrent
MIT6.00SCS11_archive.torrent 84.0 KB 

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Reviewer: stinger99 - 4.00 out of 5 stars4.00 out of 5 stars4.00 out of 5 stars4.00 out of 5 stars - September 12, 2012
Subject: MIT 6.00SC Introduction to Computer Science and Programming,
Very helpful for those who joined any of the edx computer programs.